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Learning to reinforcement learn
TLDR
In recent years deep reinforcement learning (RL) systems have attained superhuman performance in a number of challenging task domains. Expand
Reconciling reinforcement learning models with behavioral extinction and renewal: implications for addiction, relapse, and problem gambling.
Because learned associations are quickly renewed following extinction, the extinction process must include processes other than unlearning. However, reinforcement learning models, such as theExpand
Prefrontal cortex as a meta-reinforcement learning system
Over the past 20 years, neuroscience research on reward-based learning has converged on a canonical model, under which the neurotransmitter dopamine ‘stamps in’ associations between situations,Expand
Reinforcement Learning, Fast and Slow
Deep reinforcement learning (RL) methods have driven impressive advances in artificial intelligence in recent years, exceeding human performance in domains ranging from Atari to Go to no-limit poker.Expand
What Is a Cognitive Map? Organizing Knowledge for Flexible Behavior
TLDR
Cognitive map-like representations observed in a spatial context may be an instance of general coding mechanisms capable of organizing knowledge of all kinds. Expand
Single- and cross-commodity discounting among cocaine addicts: the commodity and its temporal location determine discounting rate
RationaleIntertemporal choice has provided important insights into understanding addiction, predicted drug-dependence status, and outcomes of treatment interventions. However, such analyses haveExpand
A distributional code for value in dopamine-based reinforcement learning
TLDR
We propose a model of reinforcement learning in which the brain represents possible future rewards not as a single mean of stochastic outcomes, as in the canonical model, but instead as a probability distribution, effectively representing multiple future outcomes simultaneously and in parallel. Expand
Harm to others outweighs harm to self in moral decision making
Significance Concern for the welfare of others is a key component of moral decision making and is disturbed in antisocial and criminal behavior. However, little is known about how people evaluate theExpand
Information Processing in Decision-Making Systems
Decisions result from an interaction between multiple functional systems acting in parallel to process information in very different ways, each with strengths and weaknesses. In this review, theExpand
Moral transgressions corrupt neural representations of value
Moral systems universally prohibit harming others for personal gain. However, we know little about how such principles guide moral behavior. Using a task that assesses the financial cost participantsExpand
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